Abstract:
There are 1.8 billion Muslims around the world who pray five times a day. Using the
Human Activity Recognition Method, we can get a variety of benefits for diagnosing
prayer activities, such as automatically switching smartphones to silent mode during
prayers. Using smartphones, we can get this help Smartphones currently have many
accelerometers, gyroscopes, magnetometers, and other sensors built-in. These sensors can
be used to detect the activity of prayers based on artificial intelligence because, during the
prayers, people perform certain activities and perform the prayers. In this paper, we have
tried to determine the activity of prayers using the sensors of smartphones. Although there
are many sensors in the smartphone, we have used three sensors namely accelerometer,
gyroscope, and magnetometer respectively. The use of an accelerometer gyroscope as well
as a magnetometer sensor has helped in getting the activities of the prayer accurately. We
used machine learning to accurately predict the five prayer activities in this research
project, with a maximum accuracy of 99.43%. We have seen that prayer activities are
performed with different body movements Our model can diagnose this very well. We have
proven that it is possible to increase this accuracy by using multiple sensors without using
only one sensor.
